The data used in this analysis is from the Export Standardized Tables in the SEACAR Data Discovery Interface (DDI). Documents and information available through the SEACAR DDI are owned by the data provider(s) and users are expected to provide appropriate credit following accepted citation formats. Users are encouraged to access data to maximize utilization of gained knowledge, reducing redundant research and facilitating partnerships and scientific innovation.
With respect to documents and information available from SEACAR DDI, neither the State of Florida nor the Florida Department of Environmental Protection makes any warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose arising out of the use or inability to use the data, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.
This report was funded in part, through a grant agreement from the Florida Department of Environmental Protection, Florida Coastal Management Program, by a grant provided by the Office for Coastal Management under the Coastal Zone Management Act of 1972, as amended, National Oceanic and Atmospheric Administration. The views, statements, findings, conclusions and recommendations expressed herein are those of the author(s) and do not necessarily reflect the views of the State of Florida, NOAA or any of their sub agencies.
Published: 2025-07-02
Threshold filters, following the guidance of Florida Department of Environmental Protection’s (FDEP) Division of Environmental Assessment and Restoration (DEAR) are used to exclude specific results values from the SEACAR Analysis. Based on the threshold filters, Quality Assurance / Quality Control (QAQC) Flags are inserted into the SEACAR_QAQCFlagCode and SEACAR_QAQC_Description columns of the export data. The Include column indicates whether the QAQC Flag will also indicate that data are excluded from analysis. No data are excluded from the data export, but the analysis scripts can use the Include column to exclude data (1 to include, 0 to exclude).
| Parameter Name | Units | Low Threshold | High Threshold |
|---|---|---|---|
| Dissolved Oxygen | mg/L | -0.000001 | 50 |
| Dissolved Oxygen Saturation | % | -0.000001 | 500 |
| Salinity | ppt | -0.000001 | 70 |
| Turbidity | NTU | -0.000001 | 4000 |
| Water Temperature | Degrees C | -5.000000 | 45 |
| pH | None | 2.000000 | 14 |
| Parameter Name | Units | Low Threshold | High Threshold |
|---|---|---|---|
| Ammonia, Un-ionized (NH3) | mg/L | - | - |
| Ammonium, Filtered (NH4) | mg/L | - | - |
| Chlorophyll a, Corrected for Pheophytin | ug/L | - | - |
| Chlorophyll a, Uncorrected for Pheophytin | ug/L | - | - |
| Colored Dissolved Organic Matter | PCU | - | - |
| Dissolved Oxygen | mg/L | -0.000001 | 25 |
| Dissolved Oxygen Saturation | % | -0.000001 | 310 |
| Fluorescent Dissolved Organic Matter | QSE | - | - |
| Light Extinction Coefficient | m^-1 | - | - |
| NO2+3, Filtered | mg/L | - | - |
| Nitrate (NO3) | mg/L | - | - |
| Nitrite (NO2) | mg/L | - | - |
| Nitrogen, organic | mg/L | - | - |
| Phosphate, Filtered (PO4) | mg/L | - | - |
| Salinity | ppt | -0.000001 | 70 |
| Secchi Depth | m | 0.000001 | 50 |
| Specific Conductivity | mS/cm | 0.005000 | 100 |
| Total Kjeldahl Nitrogen | mg/L | - | - |
| Total Nitrogen | mg/L | - | - |
| Total Nitrogen | mg/L | - | - |
| Total Phosphorus | mg/L | - | - |
| Total Suspended Solids | mg/L | - | - |
| Turbidity | NTU | - | - |
| Water Temperature | Degrees C | 3.000000 | 40 |
| pH | None | 2.000000 | 13 |
| SEACAR QAQC Description | Include | SEACAR QAQCFlagCode |
|---|---|---|
| Exceeds maximum threshold | 0 | 2Q |
| Below minimum threshold | 0 | 4Q |
| Within threshold tolerance | 1 | 6Q |
| No defined thresholds for this parameter | 1 | 7Q |
Value qualifier codes included within the data are used to exclude certain results from the analysis. The data are retained in the data export files, but the analysis uses the Include column to filter the results.
STORET and WIN value qualifier codes
Value qualifier codes from STORET and WIN data are examined with the database and used to populate the Include column in data exports.
| Qualifier Source | Value Qualifier | Include | MDL | Description |
|---|---|---|---|---|
| STORET-WIN | H | 0 | 0 | Value based on field kit determination; results may not be accurate |
| STORET-WIN | J | 0 | 0 | Estimated value |
| STORET-WIN | V | 0 | 0 | Analyte was detected at or above method detection limit |
| STORET-WIN | Y | 0 | 0 |
Discrete Water Quality Value Qualifiers
The following value qualifiers are highlighted in the Discrete Water Quality section of this report. An exception is made for Program 476 - Charlotte Harbor Estuaries Volunteer Water Quality Monitoring Network and data flagged with Value Qualifier H are included for this program only.
H - Value based on field kit determiniation; results may not be accurate. This code shall be used if a field screening test (e.g., field gas chromatograph data, immunoassay, or vendor-supplied field kit) was used to generate the value and the field kit or method has not been recognized by the Department as equivalent to laboratory methods.
I - The reported value is greater than or equal to the laboratory method detection limit but less than the laboratory practical quantitation limit.
Q - Sample held beyond the accepted holding time. This code shall be used if the value is derived from a sample that was prepared or analyzed after the approved holding time restrictions for sample preparation or analysis.
S - Secchi disk visible to bottom of waterbody. The value reported is the depth of the waterbody at the location of the Secchi disk measurement.
U - Indicates that the compound was analyzed for but not detected. This symbol shall be used to indicate that the specified component was not detected. The value associated with the qualifier shall be the laboratory method detection limit. Unless requested by the client, less than the method detection limit values shall not be reported
Systemwide Monitoring Program (SWMP) value qualifier codes
Value qualifier codes from the SWMP continuous program are examined with the database and used to populate the Include column in data exports. SWMP Qualifier Codes are indicated by QualifierSource=SWMP.
| Qualifier Source | Value Qualifier | Include | Description |
|---|---|---|---|
| SWMP | -1 | 1 | Optional parameter not collected |
| SWMP | -2 | 0 | Missing data |
| SWMP | -3 | 0 | Data rejected due to QA/QC |
| SWMP | -4 | 0 | Outside low sensor range |
| SWMP | -5 | 0 | Outside high sensor range |
| SWMP | 0 | 1 | Passed initial QA/QC checks |
| SWMP | 1 | 0 | Suspect data |
| SWMP | 2 | 1 | Reserved for future use |
| SWMP | 3 | 1 | |
| SWMP | 4 | 1 | Historical: Pre-auto QA/QC |
| SWMP | 5 | 1 | Corrected data |
The water column habitat extends from the water’s surface to the bottom sediments, and it’s where fish, dolphins, crabs and people swim! So much life makes its home in the water column that the health of marine and coastal ecosystems, as well as human economies, depend on the condition of this vulnerable habitat. Local patterns of rainfall, temperature, winds and currents can rapidly change the condition of the water column, while global influences such as El Niño/La Niña, large-scale fluctuation in sea temperatures and climate change can have long-term effects. Inputs from the prosperity of our day-to-day lives including farming, mining and forestry, and emissions from power generation, automobiles and water treatment can also alter the health of the water column. Acting alone or together, each input can have complex and lasting effects on habitats and ecosystems.
SEACAR evaluates water column health with several essential parameters.
These include nutrient surveys of nitrogen and phosphorus, and water
quality assessments of salinity, dissolved oxygen, pH, and water
temperature. Water clarity is evaluated with Secchi depth, turbidity,
levels of chlorophyll a, total suspended solids, and colored dissolved
organic matter. Additionally, the richness of nekton is indicated by the
abundance of free-swimming fishes and macroinvertebrates like crabs and
shrimps.
Indicators must have a minimum of five to ten years, depending on the habitat, of data within the geographic range of the analysis to be included in the analysis. Ten years of data are required for discrete parameters, and five years of data are required for continuous parameters. If there are insufficient years of data, the number of years of data available will be noted and labeled as “insufficient data to conduct analysis”. Further, for the preferred Seasonal Kendall-Tau test, there must be data from at least two months in common across at least two consecutive years within the RCP managed area being analyzed. Values that pass both of these tests will be included in the analysis and be labeled as Use_In_Analysis = TRUE. Any that fail either test will be excluded from the analyses and labeled as Use_In_Analysis = FALSE. The points for all Water Column plots displayed in this section are monthly averages. Trend significance will be denoted as “Significant Trend” (when p < 0.05), or “Non-significant Trend” (when p >= 0.05). Any parameters with insufficient data to perform Seasonal Kendall-Tau test will have their monthly averages plotted without a corresponding trend line.
The following files were used in the discrete analysis:
Combined_WQ_WC_NUT_Chlorophyll_a_corrected_for_pheophytin-2025-Mar-06.txt
Combined_WQ_WC_NUT_Chlorophyll_a_uncorrected_for_pheophytin-2025-Mar-06.txt
Combined_WQ_WC_NUT_Colored_dissolved_organic_matter_CDOM-2025-Mar-06.txt
Combined_WQ_WC_NUT_Dissolved_Oxygen-2025-Mar-06.txt
Combined_WQ_WC_NUT_Dissolved_Oxygen_Saturation-2025-Mar-06.txt
Combined_WQ_WC_NUT_pH-2025-Mar-06.txt
Combined_WQ_WC_NUT_Salinity-2025-Mar-06.txt
Combined_WQ_WC_NUT_Secchi_Depth-2025-Mar-06.txt
Combined_WQ_WC_NUT_Total_Nitrogen-2025-Mar-06.txt
Combined_WQ_WC_NUT_Total_Phosphorus-2025-Mar-06.txt
Combined_WQ_WC_NUT_Total_Suspended_Solids_TSS-2025-Mar-06.txt
Combined_WQ_WC_NUT_Turbidity-2025-Mar-06.txt
Combined_WQ_WC_NUT_Water_Temperature-2025-Mar-06.txt
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | Significantly increasing trend | 2048 | 17 | 2004 - 2024 | 0.62 | 0.2827 | 0.2309 | 0.0411 | 0 |
Monthly average chlorophyll a, corrected for pheophytin, increased by 0.04 µg/L per year, indicating a decrease in water clarity.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 5002 | 1943 | 2004 | 2024 |
| 514 | 198 | 2018 | 2024 |
Program names:
514 - Florida LAKEWATCH Program1
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | No significant trend | 21249 | 36 | 1989 - 2024 | 0.2973 | 0.0554 | 0.4152 | 0.0022 | 0.1261 |
Chlorophyll a, uncorrected for pheophytin, showed no detectable trend between 1989 and 2024.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 16110 | 1995 | 2023 |
| 3 | 4011 | 1998 | 2024 |
| 514 | 2819 | 1998 | 2024 |
| 509 | 1418 | 1989 | 2008 |
| 5002 | 987 | 2001 | 2024 |
| 60 | 345 | 1993 | 2016 |
| 103 | 154 | 2000 | 2021 |
| 118 | 28 | 2000 | 2010 |
| 115 | 28 | 2000 | 2004 |
Program names:
3 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Synoptic Shipboard Surveys3
60 - Southeast Area Monitoring and Assessment Program (SEAMAP)
- Gulf of Mexico Fall & Summer Shrimp/Groundfish Survey4
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
118 - National Aquatic Resource Surveys, National Coastal
Condition Assessment7
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
514 - Florida LAKEWATCH Program1
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | Significantly increasing trend | 1025 | 24 | 2001 - 2024 | 6 | 0.2457 | 5.4354 | 0.1048 | 0.0003 |
Monthly average colored dissolved organic matter increased by 0.1 PCU per year, indicating a decrease in water clarity.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 514 | 1025 | 2001 | 2024 |
Program names:
514 - Florida LAKEWATCH Program1
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Field | Significantly decreasing trend | 47232 | 41 | 1970 - 2024 | 6.3 | -0.0912 | 6.6235 | -0.0063 | 0.0051 |
Monthly average dissolved oxygen decreased by 0.01 mg/L per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 32169 | 1995 | 2023 |
| 5002 | 5155 | 2003 | 2024 |
| 509 | 2701 | 1989 | 2008 |
| 69 | 1743 | 1997 | 2022 |
| 60 | 1592 | 1993 | 2016 |
| 95 | 1560 | 1994 | 2018 |
| 4049 | 1024 | 2006 | 2023 |
| 103 | 601 | 1970 | 2021 |
| 3000 | 377 | 2015 | 2018 |
| 118 | 104 | 2000 | 2021 |
| 899 | 93 | 2014 | 2015 |
| 115 | 89 | 2000 | 2004 |
| 4057 | 59 | 2015 | 2018 |
| 102 | 42 | 1996 | 2000 |
Program names:
60 - Southeast Area Monitoring and Assessment Program
(SEAMAP) - Gulf of Mexico Fall & Summer Shrimp/Groundfish
Survey4
69 - Fisheries-Independent Monitoring (FIM) Program10
95 - Harmful Algal Bloom Marine Observation Network11
102 - National Status and Trends Mussel Watch12
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
118 - National Aquatic Resource Surveys, National Coastal
Condition Assessment7
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
899 - USGS Coral Reef Ecosystem Studies (CREST) Project13
3000 - Florida Keys Water Watch14
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
4057 - Biscayne Bay Water Watch16
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Field | Significantly increasing trend | 29283 | 30 | 1995 - 2024 | 94.7731 | 0.1922 | 91.9441 | 0.18 | 0 |
Monthly average dissolved oxygen saturation increased by 0.18% per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 25419 | 1995 | 2020 |
| 5002 | 3907 | 2009 | 2024 |
| 102 | 18 | 1996 | 1996 |
| 95 | 1 | 2017 | 2017 |
Program names:
95 - Harmful Algal Bloom Marine Observation Network11
102 - National Status and Trends Mussel Watch12
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Field | Significantly decreasing trend | 9785 | 30 | 1970 - 2024 | 8.04 | -0.167 | 8.1609 | -0.0038 | 0 |
Monthly average pH decreased by less than 0.01 pH units per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 5002 | 5287 | 2003 | 2024 |
| 69 | 1733 | 1997 | 2022 |
| 4049 | 1103 | 2005 | 2023 |
| 509 | 545 | 2002 | 2008 |
| 3000 | 377 | 2015 | 2018 |
| 3 | 287 | 2009 | 2012 |
| 95 | 142 | 1994 | 2018 |
| 297 | 114 | 2003 | 2011 |
| 115 | 89 | 2000 | 2004 |
| 899 | 88 | 2014 | 2015 |
| 103 | 86 | 1970 | 2021 |
| 4057 | 59 | 2015 | 2018 |
Program names:
3 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Synoptic Shipboard Surveys3
69 - Fisheries-Independent Monitoring (FIM) Program10
95 - Harmful Algal Bloom Marine Observation Network11
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
899 - USGS Coral Reef Ecosystem Studies (CREST) Project13
3000 - Florida Keys Water Watch14
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
4057 - Biscayne Bay Water Watch16
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| All | No significant trend | 54590 | 47 | 1955 - 2024 | 36.19 | 0.0275 | 34.8062 | 0.0072 | 0.4344 |
Salinity showed no detectable trend between 1955 and 2024.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 31841 | 1995 | 2023 |
| 5002 | 5291 | 2003 | 2024 |
| 3 | 4343 | 1998 | 2024 |
| 509 | 2581 | 1989 | 2008 |
| 965 | 2317 | 2005 | 2011 |
| 95 | 1889 | 1955 | 2018 |
| 69 | 1741 | 1997 | 2022 |
| 60 | 1524 | 1993 | 2016 |
| 4049 | 1168 | 2005 | 2023 |
| 62 | 1142 | 1993 | 2019 |
| 3000 | 379 | 2015 | 2018 |
| 118 | 109 | 2015 | 2021 |
| 115 | 89 | 2000 | 2004 |
| 899 | 82 | 2014 | 2015 |
| 102 | 60 | 1996 | 2000 |
| 4057 | 59 | 2015 | 2018 |
Program names:
3 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Synoptic Shipboard Surveys3
60 - Southeast Area Monitoring and Assessment Program (SEAMAP)
- Gulf of Mexico Fall & Summer Shrimp/Groundfish Survey4
62 - Southeast Area Monitoring and Assessment Program (SEAMAP)
- Gulf of Mexico Reef Fish Survey17
69 - Fisheries-Independent Monitoring (FIM) Program10
95 - Harmful Algal Bloom Marine Observation Network11
102 - National Status and Trends Mussel Watch12
115 - Environmental Monitoring Assessment Program6
118 - National Aquatic Resource Surveys, National Coastal
Condition Assessment7
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
899 - USGS Coral Reef Ecosystem Studies (CREST) Project13
965 - South Florida Seagrass Fish and Invertebrate Assessment
Network18
3000 - Florida Keys Water Watch14
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
4057 - Biscayne Bay Water Watch16
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Field | No significant trend | 5051 | 30 | 1993 - 2024 | -2.1336 | 0.0036 | -2.4543 | 0.0007 | 0.8805 |
Secchi depth showed no detectable trend between 1993 and 2024.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 514 | 2500 | 1998 | 2024 |
| 69 | 1750 | 1997 | 2022 |
| 3000 | 373 | 2015 | 2018 |
| 5002 | 352 | 2005 | 2022 |
| 4049 | 252 | 2005 | 2023 |
| 60 | 37 | 1993 | 2002 |
| 115 | 21 | 2000 | 2004 |
Program names:
60 - Southeast Area Monitoring and Assessment Program
(SEAMAP) - Gulf of Mexico Fall & Summer Shrimp/Groundfish
Survey4
69 - Fisheries-Independent Monitoring (FIM) Program10
115 - Environmental Monitoring Assessment Program6
514 - Florida LAKEWATCH Program1
3000 - Florida Keys Water Watch14
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
5002 - Florida STORET / WIN2
Total Nitrogen Calculation:
The logic for calculated Total Nitrogen was provided by Kevin O’Donnell and colleagues at FDEP (with the help of Jay Silvanima, Watershed Monitoring Section). The following logic is used, in this order, based on the availability of specific nitrogen components.
Additional Information:
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | Significantly decreasing trend | 34570 | 36 | 1989 - 2024 | 0.146 | -0.2631 | 0.257 | -0.0041 | 0 |
Monthly average total nitrogen decreased by less than 0.01 mg/L per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 26153 | 1995 | 2023 |
| 5002 | 4797 | 1998 | 2024 |
| 514 | 2907 | 1998 | 2024 |
| 509 | 1424 | 1989 | 2008 |
| 103 | 149 | 2000 | 2006 |
| 115 | 28 | 2000 | 2004 |
Program names:
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
514 - Florida LAKEWATCH Program1
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | Significantly decreasing trend | 32282 | 37 | 1970 - 2024 | 0.0059 | -0.0865 | 0.0074 | 0 | 0.0125 |
Monthly average total phosphorus decreased by less than 0.01 mg/L per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 26170 | 1995 | 2023 |
| 514 | 2914 | 1998 | 2024 |
| 5002 | 2121 | 2005 | 2024 |
| 509 | 1425 | 1989 | 2008 |
| 103 | 182 | 1970 | 2021 |
| 115 | 28 | 2000 | 2004 |
Program names:
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
514 - Florida LAKEWATCH Program1
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | Significantly decreasing trend | 536 | 18 | 2007 - 2024 | 12 | -0.5976 | 50.053 | -4.7089 | 0 |
Monthly average total suspended solids decreased by 4.71 mg/L per year, indicating an increase in water clarity.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 3 | 1391 | 2001 | 2012 |
| 5002 | 548 | 2007 | 2024 |
| 103 | 1 | 2020 | 2020 |
Program names:
3 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Synoptic Shipboard Surveys3
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Lab | No significant trend | 3529 | 34 | 1991 - 2024 | 0.705 | -0.0203 | 0.8692 | -0.0015 | 0.5837 |
Turbidity showed no detectable trend between 1991 and 2024.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 26741 | 1995 | 2023 |
| 5002 | 2144 | 1994 | 2024 |
| 509 | 1404 | 1991 | 2008 |
| 965 | 1157 | 2005 | 2011 |
| 3000 | 370 | 2015 | 2018 |
| 103 | 117 | 2005 | 2021 |
Program names:
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
965 - South Florida Seagrass Fish and Invertebrate Assessment
Network18
3000 - Florida Keys Water Watch14
5002 - Florida STORET / WIN2
Seasonal Kendall-Tau Trend Analysis
| Activity Type | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Field | Significantly increasing trend | 53391 | 49 | 1955 - 2024 | 27.1769 | 0.2247 | 24.6007 | 0.0269 | 0 |
Monthly average water temperature increased by 0.03°C per year.
| ProgramID | N_Data | YearMin | YearMax |
|---|---|---|---|
| 297 | 31793 | 1995 | 2023 |
| 5002 | 5723 | 2003 | 2024 |
| 509 | 2601 | 1989 | 2008 |
| 965 | 2317 | 2005 | 2011 |
| 95 | 1957 | 1955 | 2018 |
| 3 | 1853 | 1998 | 2012 |
| 69 | 1776 | 1997 | 2022 |
| 60 | 1582 | 1993 | 2016 |
| 4049 | 1168 | 2005 | 2023 |
| 982 | 1129 | 2014 | 2023 |
| 103 | 875 | 1970 | 2021 |
| 3000 | 374 | 2015 | 2018 |
| 115 | 89 | 2000 | 2004 |
| 899 | 85 | 2014 | 2015 |
| 4057 | 59 | 2015 | 2018 |
| 102 | 43 | 1996 | 2000 |
Program names:
3 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Synoptic Shipboard Surveys3
60 - Southeast Area Monitoring and Assessment Program (SEAMAP)
- Gulf of Mexico Fall & Summer Shrimp/Groundfish Survey4
69 - Fisheries-Independent Monitoring (FIM) Program10
95 - Harmful Algal Bloom Marine Observation Network11
102 - National Status and Trends Mussel Watch12
103 - EPA STOrage and RETrieval Data Warehouse
(STORET)/WQX5
115 - Environmental Monitoring Assessment Program6
297 - Florida Keys National Marine Sanctuary Water Quality
Monitoring Project8
509 - SERC Water Quality Monitoring Network9
899 - USGS Coral Reef Ecosystem Studies (CREST) Project13
965 - South Florida Seagrass Fish and Invertebrate Assessment
Network18
982 - Florida Keys Bleach Watch19
3000 - Florida Keys Water Watch14
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
4057 - Biscayne Bay Water Watch16
5002 - Florida STORET / WIN2
The following files were used in the continuous analysis:
Combined_WQ_WC_NUT_cont_Dissolved_Oxygen_SE-2025-Mar-06.txt
Combined_WQ_WC_NUT_cont_Dissolved_Oxygen_Saturation_SE-2025-Mar-06.txt
Combined_WQ_WC_NUT_cont_pH_SE-2025-Mar-06.txt
Combined_WQ_WC_NUT_cont_Salinity_SE-2025-Mar-06.txt
Combined_WQ_WC_NUT_cont_Turbidity_SE-2025-Mar-06.txt
Combined_WQ_WC_NUT_cont_Water_Temperature_SE-2025-Mar-06.txt
Continuous monitoring locations in Florida Keys National Marine Sanctuary
| ProgramID | ProgramLocationID | Years of Data | Use in Analysis | Parameters |
|---|---|---|---|---|
| 2 | 1B | 6 | TRUE | Sal , TempW |
| 5 | KYWF1 | 20 | TRUE | TempW |
| 5 | LONF1 | 28 | TRUE | TempW |
| 5 | MLRF1 | 33 | TRUE | TempW |
| 5 | SANF1 | 15 | TRUE | TempW |
| 5 | SMKF1 | 21 | TRUE | TempW |
| 7 | 245323080410100 | 3 | FALSE | Sal , TempW |
| 7 | 245622080364200 | 3 | FALSE | Sal , TempW |
| 296 | 214 | 18 | TRUE | TempW |
| 296 | 215 | 16 | TRUE | TempW |
| 296 | 216 | 17 | TRUE | TempW |
| 296 | 220 | 17 | TRUE | TempW |
| 296 | 223 | 18 | TRUE | TempW |
| 296 | 225 | 18 | TRUE | TempW |
| 296 | 227 | 17 | TRUE | TempW |
| 296 | 235 | 18 | TRUE | TempW |
| 296 | 237 | 18 | TRUE | TempW |
| 296 | 239 | 17 | TRUE | TempW |
| 296 | 241 | 18 | TRUE | TempW |
| 296 | 243 | 18 | TRUE | TempW |
| 296 | 248 | 18 | TRUE | TempW |
| 296 | 255 | 18 | TRUE | TempW |
| 296 | 260 | 18 | TRUE | TempW |
| 296 | 267 | 18 | TRUE | TempW |
| 296 | 269 | 18 | TRUE | TempW |
| 296 | 271 | 18 | TRUE | TempW |
| 296 | 273 | 18 | TRUE | TempW |
| 296 | 276 | 18 | TRUE | TempW |
| 296 | 284 | 18 | TRUE | TempW |
| 296 | 285 | 18 | TRUE | TempW |
| 296 | 287 | 18 | TRUE | TempW |
| 296 | 291 | 18 | TRUE | TempW |
| 296 | 294 | 18 | TRUE | TempW |
| 296 | 296 | 18 | TRUE | TempW |
| 296 | 305 | 18 | TRUE | TempW |
| 296 | 307 | 18 | TRUE | TempW |
| 296 | 309 | 18 | TRUE | TempW |
| 296 | 314 | 18 | TRUE | TempW |
| 296 | 500 | 8 | TRUE | TempW |
| 296 | 501 | 7 | TRUE | TempW |
| 296 | 502 | 4 | FALSE | TempW |
| 296 | 503 | 1 | FALSE | TempW |
| 296 | 504 | 1 | FALSE | TempW |
| 296 | 506 | 8 | TRUE | TempW |
| 296 | 507 | 8 | TRUE | TempW |
| 296 | 508 | 8 | TRUE | TempW |
| 296 | 509 | 8 | TRUE | TempW |
| 296 | SB | 19 | TRUE | TempW |
| 899 | Crocker | 10 | TRUE | TempW |
| 899 | Molasses | 5 | TRUE | TempW |
| 899 | Sombrero | 14 | TRUE | TempW |
| 986 | 10 | 3 | FALSE | TempW |
| 986 | 11 | 20 | TRUE | TempW |
| 986 | 12 | 15 | TRUE | TempW |
| 986 | 14 | 21 | TRUE | TempW |
| 986 | 15 | 17 | TRUE | TempW |
| 986 | 18 | 7 | TRUE | TempW |
| 986 | 21 | 7 | TRUE | TempW |
| 986 | 22 | 14 | TRUE | TempW |
| 986 | 23 | 11 | TRUE | TempW |
| 986 | 24 | 13 | TRUE | TempW |
| 986 | 25 | 13 | TRUE | TempW |
| 986 | 26 | 14 | TRUE | TempW |
| 986 | 30 | 11 | TRUE | TempW |
| 986 | 32 | 20 | TRUE | TempW |
| 986 | 33 | 7 | TRUE | TempW |
| 986 | 34 | 21 | TRUE | TempW |
| 986 | 35 | 17 | TRUE | TempW |
| 986 | 36 | 16 | TRUE | TempW |
| 986 | 37 | 7 | TRUE | TempW |
| 986 | 38 | 21 | TRUE | TempW |
| 986 | 39 | 5 | TRUE | TempW |
| 986 | 40 | 21 | TRUE | TempW |
| 986 | 50 | 10 | TRUE | TempW |
| 986 | 51 | 20 | TRUE | TempW |
| 986 | 52 | 15 | TRUE | TempW |
| 986 | 53 | 15 | TRUE | TempW |
| 986 | 54 | 11 | TRUE | TempW |
| 986 | 55 | 21 | TRUE | TempW |
| 986 | 56 | 17 | TRUE | TempW |
| 986 | 57 | 15 | TRUE | TempW |
| 986 | 58 | 9 | TRUE | TempW |
| 986 | 59 | 21 | TRUE | TempW |
| 986 | 60 | 14 | TRUE | TempW |
| 986 | 61 | 7 | TRUE | TempW |
| 986 | 70 | 10 | TRUE | TempW |
| 986 | 72 | 15 | TRUE | TempW |
| 986 | 73 | 15 | TRUE | TempW |
| 986 | 74 | 11 | TRUE | TempW |
| 986 | 75 | 13 | TRUE | TempW |
| 986 | 76 | 14 | TRUE | TempW |
| 986 | 77 | 15 | TRUE | TempW |
| 986 | 78 | 9 | TRUE | TempW |
| 986 | 79 | 16 | TRUE | TempW |
| 986 | 80 | 14 | TRUE | TempW |
| 986 | 81 | 7 | TRUE | TempW |
| 986 | 83 | 17 | TRUE | TempW |
| 989 | FKNMS_200YR_HD | 12 | TRUE | TempW |
| 989 | FKNMS_7MILE_BR | 20 | TRUE | TempW |
| 989 | FKNMS_9FT_SHOAL | 21 | TRUE | TempW |
| 989 | FKNMS_ALLIGATOR | 21 | TRUE | TempW |
| 989 | FKNMS_BHONDA_BR | 22 | TRUE | TempW |
| 989 | FKNMS_BOCA_GRND | 23 | TRUE | TempW |
| 989 | FKNMS_BULLARD | 18 | TRUE | TempW |
| 989 | FKNMS_CARD_SND | 6 | TRUE | TempW |
| 989 | FKNMS_CARYSFORT | 17 | TRUE | TempW |
| 989 | FKNMS_DIEGO_TER | 5 | TRUE | TempW |
| 989 | FKNMS_ELPIS | 8 | TRUE | TempW |
| 989 | FKNMS_GRECIAN | 21 | TRUE | TempW |
| 989 | FKNMS_HARBORKEY | 6 | TRUE | TempW |
| 989 | FKNMS_HEN&CHIX | 23 | TRUE | TempW |
| 989 | FKNMS_KW_CHANL | 22 | TRUE | TempW |
| 989 | FKNMS_LONG_KEY | 21 | TRUE | TempW |
| 989 | FKNMS_LOOE_BACK | 23 | TRUE | TempW |
| 989 | FKNMS_LOOE_BUOY5 | 11 | TRUE | TempW |
| 989 | FKNMS_LOOE_ISELIN | 16 | TRUE | TempW |
| 989 | FKNMS_MAITLAND | 4 | FALSE | TempW |
| 989 | FKNMS_MOLASSES | 13 | TRUE | TempW |
| 989 | FKNMS_NEWGROUND | 15 | TRUE | TempW |
| 989 | FKNMS_PILLAR | 11 | TRUE | TempW |
| 989 | FKNMS_SAND_KEY | 21 | TRUE | TempW |
| 989 | FKNMS_SMITH_SHL | 15 | TRUE | TempW |
| 989 | FKNMS_SNAKE_CRK | 19 | TRUE | TempW |
| 989 | FKNMS_SOMBRERO | 15 | TRUE | TempW |
| 989 | FKNMS_SPRIGGER | 15 | TRUE | TempW |
| 989 | FKNMS_TENN_REEF | 17 | TRUE | TempW |
| 989 | FKNMS_WELLWOOD | 8 | TRUE | TempW |
| 989 | FKNMS_WS_BUOY16 | 3 | FALSE | TempW |
| 989 | FKNMS_WS_JACKYL | 9 | TRUE | TempW |
| 989 | FKNMS_W_SAMBO | 6 | TRUE | TempW |
| 10004 | FKCB | 1 | FALSE | DO , DOS , pH , Sal , Turb , TempW |
| 10004 | FKLK | 1 | FALSE | DO , DOS , pH , Sal , Turb , TempW |
Program names:
2 - Atlantic Oceanographic and Meteorological Laboratory
(AOML) South Florida Program Moored Instrument Array20
5 - National Data Buoy Center21
7 - National Water Information System22
296 - Florida Keys National Marine Sanctuary Seagrass
Monitoring Project23
899 - USGS Coral Reef Ecosystem Studies (CREST) Project13
986 - Water Temperature on Coral Reefs in the Florida Keys24
989 - Continuous Bottom Temperature Measurements along the
Florida Reef Tract25
10004 - Florida Keys Aquatic Preserves Continuous Water Quality
Monitoring26
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKLK | Insufficient data to calculate trend | 21525 | 1 | 2024 - 2024 | 6.2 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16262 | 1 | 2024 - 2024 | 6.8 | - | - | - | - |
There was insufficient data to fit a model for two locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKLK | Insufficient data to calculate trend | 21525 | 1 | 2024 - 2024 | 91.9 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16263 | 1 | 2024 - 2024 | 103.3 | - | - | - | - |
There was insufficient data to fit a model for two locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKLK | Insufficient data to calculate trend | 21517 | 1 | 2024 - 2024 | 8.1 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16263 | 1 | 2024 - 2024 | 8.2 | - | - | - | - |
There was insufficient data to fit a model for two locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| 1B | No significant trend | 86204 | 6 | 2003 - 2008 | 36.07 | 0.24 | 35.68 | 0.17 | 0.05 |
| 245323080410100 | Insufficient data to calculate trend | 746 | 3 | 2002 - 2004 | 35.00 | - | - | - | - |
| 245622080364200 | Insufficient data to calculate trend | 764 | 3 | 2002 - 2004 | 35.00 | - | - | - | - |
| FKLK | Insufficient data to calculate trend | 21517 | 1 | 2024 - 2024 | 36.10 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16258 | 1 | 2024 - 2024 | 36.50 | - | - | - | - |
No detectable change in monthly average salinity was observed at one location. There was insufficient data to fit a model for four locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKLK | Insufficient data to calculate trend | 21399 | 1 | 2024 - 2024 | 6 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16240 | 1 | 2024 - 2024 | 4 | - | - | - | - |
There was insufficient data to fit a model for two locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| 1B | Significantly increasing trend | 86204 | 6 | 2003 - 2008 | 26.38 | 0.26 | 25.73 | 0.16 | 0.04 |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| SMKF1 | Significantly increasing trend | 154326 | 21 | 1988 - 2008 | 26.8 | 0.34 | 26.24 | 0.06 | 0.00 |
| KYWF1 | Significantly increasing trend | 1441302 | 20 | 2005 - 2024 | 27.6 | 0.31 | 26.65 | 0.07 | 0.00 |
| LONF1 | No significant trend | 205971 | 28 | 1992 - 2019 | 26.6 | 0.07 | 26.34 | 0.01 | 0.08 |
| MLRF1 | Significantly increasing trend | 256798 | 33 | 1987 - 2019 | 26.5 | 0.10 | 26.49 | 0.01 | 0.00 |
| SANF1 | No significant trend | 117833 | 15 | 1991 - 2005 | 26.7 | -0.03 | 26.69 | 0.00 | 0.62 |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| 245323080410100 | Insufficient data to calculate trend | 791 | 3 | 2002 - 2004 | 27.9 | - | - | - | - |
| 245622080364200 | Insufficient data to calculate trend | 853 | 3 | 2002 - 2004 | 28.3 | - | - | - | - |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| 241 | Significantly increasing trend | 127914 | 18 | 2002 - 2019 | 27.26 | 0.27 | 25.91 | 0.09 | 0 |
| 243 | Significantly increasing trend | 121593 | 18 | 2002 - 2019 | 26.62 | 0.3 | 26 | 0.07 | 0 |
| 255 | Significantly increasing trend | 119939 | 18 | 2002 - 2019 | 26.35 | 0.24 | 25.73 | 0.07 | 0 |
| 260 | Significantly increasing trend | 97832 | 16 | 2002 - 2019 | 27.07 | 0.28 | 26.22 | 0.08 | 0 |
| 284 | Significantly increasing trend | 123977 | 17 | 2002 - 2019 | 26.86 | 0.28 | 25.14 | 0.09 | 0 |
| 285 | Significantly increasing trend | 121423 | 18 | 2002 - 2019 | 26.86 | 0.25 | 26.17 | 0.07 | 0 |
| 287 | Significantly increasing trend | 133008 | 18 | 2002 - 2019 | 26.87 | 0.29 | 25.84 | 0.08 | 0 |
| 291 | Significantly increasing trend | 116240 | 18 | 2002 - 2019 | 26.38 | 0.26 | 25.72 | 0.09 | 0 |
| 294 | Significantly increasing trend | 112348 | 18 | 2002 - 2019 | 26.92 | 0.27 | 25.52 | 0.09 | 0 |
| 239 | Significantly increasing trend | 111523 | 17 | 2002 - 2018 | 26.92 | 0.24 | 25.96 | 0.07 | 0 |
| 267 | Significantly increasing trend | 99735 | 18 | 2002 - 2019 | 26.57 | 0.24 | 25.64 | 0.05 | 0 |
| 269 | Significantly increasing trend | 106458 | 17 | 2002 - 2019 | 26.74 | 0.21 | 26.02 | 0.05 | 0 |
| 271 | Significantly increasing trend | 133627 | 18 | 2002 - 2019 | 26.92 | 0.26 | 25.77 | 0.07 | 0 |
| 273 | Significantly increasing trend | 129817 | 18 | 2002 - 2019 | 27.16 | 0.24 | 26.16 | 0.05 | 0 |
| 276 | Significantly increasing trend | 123833 | 18 | 2002 - 2019 | 26.87 | 0.21 | 26.15 | 0.05 | 0 |
| 216 | Significantly increasing trend | 98535 | 17 | 2002 - 2018 | 26.26 | 0.31 | 25.86 | 0.06 | 0 |
| 220 | Significantly increasing trend | 126033 | 17 | 2003 - 2019 | 26.52 | 0.25 | 25.94 | 0.06 | 0 |
| 223 | Significantly increasing trend | 133082 | 18 | 2002 - 2019 | 26.89 | 0.3 | 25.84 | 0.08 | 0 |
| 225 | Significantly increasing trend | 117692 | 17 | 2002 - 2019 | 26.82 | 0.32 | 26.32 | 0.06 | 0 |
| 227 | Significantly increasing trend | 105351 | 17 | 2003 - 2019 | 26.67 | 0.29 | 26.06 | 0.08 | 0 |
| 235 | Significantly increasing trend | 128499 | 18 | 2002 - 2019 | 27.14 | 0.28 | 25.77 | 0.08 | 0 |
| 237 | Significantly increasing trend | 122250 | 18 | 2002 - 2019 | 26.38 | 0.31 | 25.74 | 0.09 | 0 |
| 296 | Significantly increasing trend | 114497 | 17 | 2002 - 2019 | 27.36 | 0.21 | 25.45 | 0.07 | 0 |
| 305 | Significantly increasing trend | 122296 | 18 | 2002 - 2019 | 26.43 | 0.22 | 26.07 | 0.06 | 0 |
| 307 | Significantly increasing trend | 110802 | 17 | 2002 - 2019 | 26.74 | 0.22 | 25.73 | 0.07 | 0 |
| SB | Significantly increasing trend | 145514 | 19 | 2001 - 2019 | 26.34 | 0.23 | 25.9 | 0.06 | 0 |
| 214 | Significantly increasing trend | 136333 | 18 | 2002 - 2019 | 26.52 | 0.27 | 25.84 | 0.07 | 0 |
| 215 | Significantly increasing trend | 133286 | 16 | 2003 - 2018 | 26.74 | 0.26 | 26.42 | 0.05 | 0 |
| 314 | Significantly increasing trend | 110686 | 18 | 2002 - 2019 | 27.41 | 0.23 | 25.63 | 0.06 | 0 |
| 309 | Significantly increasing trend | 107410 | 18 | 2002 - 2019 | 27.85 | 0.27 | 26.07 | 0.06 | 0 |
| 248 | Significantly increasing trend | 111702 | 18 | 2002 - 2019 | 26.79 | 0.31 | 25.54 | 0.08 | 0 |
| 500 | Significantly increasing trend | 69048 | 8 | 2012 - 2019 | 27.33 | 0.23 | 26.79 | 0.12 | 0.01 |
| 506 | No significant trend | 35198 | 7 | 2012 - 2019 | 27.41 | 0.04 | 27.2 | 0.05 | 0.74 |
| 507 | No significant trend | 47517 | 8 | 2012 - 2019 | 27.36 | 0.18 | 27.48 | 0.09 | 0.12 |
| 508 | No significant trend | 24021 | 6 | 2012 - 2019 | 26.67 | 0.33 | 26.54 | 0.07 | 0.29 |
| 509 | No significant trend | 38607 | 8 | 2012 - 2019 | 27.70 | 0.05 | 27.79 | 0.11 | 0.47 |
| 502 | Insufficient data to calculate trend | 22765 | 4 | 2016 - 2019 | 26.70 | - | - | - | - |
| 501 | No significant trend | 34805 | 5 | 2012 - 2018 | 27.48 | 0.11 | 27.55 | 0.05 | 0.65 |
| 503 | Insufficient data to calculate trend | 7490 | 1 | 2016 - 2016 | 28.74 | - | - | - | - |
| 504 | Insufficient data to calculate trend | 4339 | 1 | 2018 - 2018 | 29.84 | - | - | - | - |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| Sombrero | Significantly increasing trend | 459354 | 14 | 2009 - 2022 | 27.16 | 0.26 | 26.83 | 0.05 | 0.00 |
| Crocker | Significantly increasing trend | 322670 | 10 | 2013 - 2022 | 27.32 | 0.15 | 27.07 | 0.03 | 0.04 |
| Molasses | No significant trend | 140713 | 5 | 2009 - 2013 | 26.72 | -0.03 | 26.61 | -0.04 | 0.92 |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| 35 | Significantly increasing trend | 217666 | 17 | 2006 - 2022 | 26.84 | 0.22 | 26.41 | 0.05 | 0 |
| 36 | Significantly increasing trend | 192871 | 16 | 2007 - 2022 | 26.89 | 0.24 | 26.52 | 0.06 | 0 |
| 34 | Significantly increasing trend | 274006 | 21 | 2002 - 2022 | 26.74 | 0.31 | 26.19 | 0.07 | 0 |
| 56 | Significantly increasing trend | 175648 | 17 | 2006 - 2022 | 26.67 | 0.14 | 26.67 | 0.03 | 0.02 |
| 79 | Significantly increasing trend | 175394 | 16 | 2007 - 2022 | 26.79 | 0.21 | 26.56 | 0.04 | 0 |
| 53 | Significantly increasing trend | 179447 | 15 | 2008 - 2022 | 26.98 | 0.37 | 26.53 | 0.07 | 0 |
| 14 | Significantly increasing trend | 223851 | 19 | 2002 - 2022 | 26.84 | 0.24 | 26.31 | 0.06 | 0 |
| 24 | Significantly increasing trend | 111388 | 11 | 2010 - 2022 | 26.89 | 0.33 | 26.12 | 0.09 | 0 |
| 32 | Significantly increasing trend | 223104 | 18 | 2003 - 2022 | 26.69 | 0.31 | 26.09 | 0.06 | 0 |
| 40 | Significantly increasing trend | 244138 | 21 | 2002 - 2022 | 26.79 | 0.28 | 26.27 | 0.07 | 0 |
| 59 | Significantly increasing trend | 191677 | 18 | 2002 - 2022 | 26.81 | 0.27 | 26.85 | 0.05 | 0 |
| 22 | Significantly increasing trend | 171553 | 14 | 2009 - 2022 | 26.91 | 0.25 | 26.43 | 0.07 | 0 |
| 72 | Significantly increasing trend | 188119 | 15 | 2008 - 2022 | 26.77 | 0.42 | 26.42 | 0.08 | 0 |
| 15 | Significantly increasing trend | 212659 | 17 | 2006 - 2022 | 26.99 | 0.19 | 26.4 | 0.05 | 0 |
| 77 | Significantly increasing trend | 188336 | 15 | 2008 - 2022 | 26.89 | 0.27 | 26.57 | 0.07 | 0 |
| 76 | Significantly increasing trend | 168914 | 14 | 2009 - 2022 | 26.84 | 0.23 | 26.82 | 0.05 | 0 |
| 12 | Significantly increasing trend | 138064 | 13 | 2008 - 2022 | 27.16 | 0.21 | 26.39 | 0.06 | 0 |
| 57 | Significantly increasing trend | 187914 | 15 | 2008 - 2022 | 26.96 | 0.3 | 26.66 | 0.07 | 0 |
| 80 | Significantly increasing trend | 167362 | 14 | 2009 - 2022 | 26.87 | 0.21 | 26.92 | 0.05 | 0 |
| 74 | Significantly increasing trend | 130333 | 11 | 2012 - 2022 | 26.87 | 0.24 | 26.64 | 0.05 | 0 |
| 73 | Significantly increasing trend | 179435 | 15 | 2008 - 2022 | 26.74 | 0.35 | 26.49 | 0.07 | 0 |
| 58 | No significant trend | 72230 | 9 | 2014 - 2022 | 27.11 | 0.01 | 27.23 | 0.01 | 0.96 |
| 11 | Significantly increasing trend | 228643 | 18 | 2003 - 2022 | 26.81 | 0.3 | 26.1 | 0.06 | 0 |
| 55 | Significantly increasing trend | 225636 | 21 | 2002 - 2022 | 26.86 | 0.28 | 26.79 | 0.05 | 0 |
| 54 | Significantly increasing trend | 130399 | 11 | 2012 - 2022 | 27.06 | 0.25 | 26.77 | 0.06 | 0 |
| 75 | Significantly increasing trend | 144589 | 13 | 2010 - 2022 | 27.06 | 0.27 | 26.71 | 0.07 | 0 |
| 60 | Significantly increasing trend | 150013 | 14 | 2009 - 2022 | 26.94 | 0.17 | 27.07 | 0.04 | 0.01 |
| 38 | Significantly increasing trend | 256177 | 21 | 2002 - 2022 | 26.47 | 0.28 | 26.15 | 0.06 | 0 |
| 61 | No significant trend | 54044 | 7 | 2016 - 2022 | 27.06 | 0.15 | 26.58 | 0.05 | 0.15 |
| 33 | No significant trend | 38112 | 6 | 2016 - 2022 | 27.13 | 0.08 | 26.23 | 0.01 | 0.66 |
| 23 | Significantly increasing trend | 113161 | 11 | 2012 - 2022 | 27.33 | 0.19 | 26.83 | 0.07 | 0.01 |
| 83 | Significantly increasing trend | 130599 | 16 | 2006 - 2022 | 25.79 | 0.14 | 25.79 | 0.04 | 0.01 |
| 52 | Significantly increasing trend | 188237 | 15 | 2008 - 2022 | 26.92 | 0.34 | 26.63 | 0.07 | 0 |
| 39 | No significant trend | 33723 | 5 | 2018 - 2022 | 27.01 | -0.09 | 27.6 | -0.08 | 0.69 |
| 37 | No significant trend | 52521 | 7 | 2016 - 2022 | 26.74 | 0.07 | 26.3 | 0.05 | 0.47 |
| 78 | No significant trend | 87924 | 9 | 2014 - 2022 | 26.98 | 0.11 | 26.81 | 0.03 | 0.19 |
| 50 | Significantly increasing trend | 103998 | 10 | 2013 - 2022 | 27.01 | 0.23 | 26.85 | 0.05 | 0 |
| 18 | No significant trend | 44119 | 7 | 2016 - 2022 | 27.03 | 0.13 | 26.59 | 0.06 | 0.29 |
| 25 | No significant trend | 117274 | 12 | 2010 - 2022 | 27.19 | 0.08 | 27.07 | 0.03 | 0.27 |
| 26 | Significantly increasing trend | 142040 | 14 | 2009 - 2022 | 26.96 | 0.21 | 26.97 | 0.06 | 0 |
| 51 | Significantly increasing trend | 222780 | 18 | 2003 - 2022 | 26.67 | 0.31 | 26.27 | 0.06 | 0 |
| 30 | Significantly increasing trend | 116701 | 11 | 2012 - 2022 | 26.62 | 0.21 | 26.3 | 0.05 | 0.01 |
| 21 | No significant trend | 55870 | 7 | 2016 - 2022 | 27.18 | 0.13 | 26.51 | 0.04 | 0.22 |
| 81 | No significant trend | 53957 | 7 | 2016 - 2022 | 27.03 | 0.13 | 26.63 | 0.05 | 0.22 |
| 70 | Significantly increasing trend | 104819 | 10 | 2013 - 2022 | 26.91 | 0.22 | 26.73 | 0.05 | 0 |
| 10 | Insufficient data to calculate trend | 18268 | 3 | 2020 - 2022 | 27.72 | - | - | - | - |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKNMS-SMITH-SHL | No significant trend | 94527 | 10 | 1998 - 2012 | 25.45 | 0.13 | 25.99 | 0.02 | 0.19 |
| FKNMS-SAND-KEY | No significant trend | 59287 | 18 | 1990 - 2010 | 26.70 | 0.05 | 26.46 | 0.01 | 0.32 |
| FKNMS-SPRIGGER | No significant trend | 41834 | 13 | 1992 - 2006 | 26.10 | 0.02 | 25.78 | 0 | 0.86 |
| FKNMS-TENN-REEF | No significant trend | 63260 | 16 | 1990 - 2006 | 26.70 | -0.06 | 26.22 | -0.01 | 0.27 |
| FKNMS-SOMBRERO | No significant trend | 48974 | 13 | 1991 - 2005 | 26.50 | 0.13 | 26.14 | 0.03 | 0.05 |
| FKNMS-200YR-HD | No significant trend | 44601 | 12 | 1998 - 2009 | 26.10 | -0.1 | 26.45 | -0.04 | 0.17 |
| FKNMS-7MILE-BR | No significant trend | 73055 | 19 | 1991 - 2010 | 26.66 | 0.05 | 26.22 | 0.01 | 0.35 |
| FKNMS-DIEGO-TER | No significant trend | 16693 | 5 | 2002 - 2006 | 25.58 | -0.05 | 25.91 | -0.03 | 0.84 |
| FKNMS-ELPIS | No significant trend | 31035 | 8 | 2004 - 2011 | 26.35 | 0.06 | 25.9 | 0.04 | 0.53 |
| FKNMS-BHONDA-BR | No significant trend | 77111 | 22 | 1990 - 2011 | 26.60 | -0.02 | 26.67 | 0 | 0.66 |
| FKNMS-BULLARD | Significantly increasing trend | 66230 | 18 | 1992 - 2009 | 26.31 | 0.12 | 26.11 | 0.02 | 0.03 |
| FKNMS-LOOE-ISELIN | No significant trend | 194367 | 13 | 1999 - 2014 | 26.88 | 0.13 | 26.55 | 0.03 | 0.08 |
| FKNMS-PILLAR | No significant trend | 40805 | 11 | 1996 - 2006 | 26.24 | 0.02 | 26.04 | 0.01 | 0.94 |
| FKNMS-MOLASSES | No significant trend | 36146 | 13 | 1990 - 2002 | 26.70 | -0.05 | 26.74 | -0.01 | 0.48 |
| FKNMS-BOCA-GRND | No significant trend | 73434 | 17 | 1990 - 2012 | 26.14 | 0.08 | 26.04 | 0.01 | 0.17 |
| FKNMS-MAITLAND | Insufficient data to calculate trend | 12421 | 4 | 2004 - 2007 | 26.07 | - | - | - | - |
| FKNMS-CARYSFORT | No significant trend | 55001 | 16 | 1990 - 2006 | 26.40 | -0.03 | 26.38 | 0 | 0.64 |
| FKNMS-9FT-SHOAL | No significant trend | 80299 | 21 | 1990 - 2010 | 26.50 | 0 | 26.76 | 0 | 0.99 |
| FKNMS-HEN-and-CHIX | No significant trend | 72285 | 21 | 1989 - 2011 | 26.50 | -0.01 | 26.35 | 0 | 0.88 |
| FKNMS-KW-CHANL | No significant trend | 123578 | 18 | 1991 - 2012 | 26.27 | 0.1 | 26.11 | 0.02 | 0.08 |
| FKNMS-GRECIAN | No significant trend | 51723 | 18 | 1990 - 2010 | 26.65 | -0.03 | 26.48 | 0 | 0.66 |
| FKNMS-LONG-KEY | No significant trend | 69656 | 19 | 1990 - 2010 | 26.64 | -0.03 | 26.35 | -0.01 | 0.58 |
| FKNMS-WELLWOOD | No significant trend | 30427 | 8 | 2002 - 2009 | 26.43 | 0 | 26.82 | 0 | 1 |
| FKNMS-SNAKE-CRK | No significant trend | 56777 | 19 | 1989 - 2007 | 26.16 | -0.06 | 26.33 | -0.02 | 0.28 |
| FKNMS-ALLIGATOR | No significant trend | 65144 | 19 | 1990 - 2010 | 26.55 | -0.06 | 26.72 | -0.01 | 0.23 |
| FKNMS-W-SAMBO | No significant trend | 18786 | 6 | 1990 - 1995 | 26.90 | 0.09 | 26.16 | 0.03 | 0.56 |
| FKNMS-LOOE-BACK | No significant trend | 84984 | 18 | 1990 - 2012 | 26.80 | -0.06 | 26.6 | -0.01 | 0.42 |
| FKNMS-LOOE-BUOY5 | No significant trend | 35252 | 10 | 1988 - 1998 | 26.90 | 0.05 | 26.86 | 0.02 | 0.36 |
| FKNMS-NEWGROUND | No significant trend | 35329 | 12 | 1992 - 2006 | 25.49 | -0.05 | 25.73 | -0.01 | 0.52 |
| FKNMS-WS-JACKYL | No significant trend | 29557 | 9 | 1991 - 1999 | 26.40 | 0.17 | 26.96 | 0.06 | 0.09 |
| FKNMS-CARD-SND | No significant trend | 18249 | 6 | 2001 - 2006 | 26.52 | -0.05 | 27.32 | -0.05 | 0.79 |
| FKNMS-HARBORKEY | No significant trend | 15407 | 5 | 1992 - 1997 | 26.50 | 0.14 | 25.74 | 0.14 | 0.33 |
| FKNMS-WS-BUOY16 | Insufficient data to calculate trend | 8123 | 3 | 2003 - 2005 | 25.99 | - | - | - | - |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
| Station | Statistical Trend | Sample Count | Years with Data | Period of Record | Median | tau | Sen Intercept | Sen Slope | p |
|---|---|---|---|---|---|---|---|---|---|
| FKLK | Insufficient data to calculate trend | 21517 | 1 | 2024 - 2024 | 29.0 | - | - | - | - |
| FKCB | Insufficient data to calculate trend | 16263 | 1 | 2024 - 2024 | 26.8 | - | - | - | - |
At seventy-four program locations, monthly average water temperature increased between 0.01 and 0.16°C per year. No detectable change in monthly average water temperature was observed at forty-eight locations. There was insufficient data to fit a model for ten locations.
The data file used is: All_SAV_Parameters-2025-Mar-06.txt
Submerged aquatic vegetation (SAV) refers to plants and plant-like macroalgae species that live entirely underwater. The two primary categories of SAV inhabiting Florida estuaries are benthic macroalgae and seagrasses. They often grow together in dense beds or meadows that carpet the seafloor. Macroalgae include multicellular species of green, red and brown algae that often live attached to the substrate by a holdfast. They tend to grow quickly and can tolerate relatively high nutrient levels, making them a threat to seagrasses and other benthic habitats in areas with poor water quality. In contrast, seagrasses are grass-like, vascular, flowering plants that are attached to the seafloor by extensive root systems. Seagrasses occur throughout the coastal areas of Florida, including protected bays and lagoons as well as deeper offshore waters on the continental shelf. Seagrasses have taken advantage of the broad, shallow shelf and clear water to produce two of the most extensive seagrass beds anywhere in continental North America.
Percent Cover measures the fraction of an area of seafloor that is covered by SAV, usually estimated by evaluating multiple small areas of seafloor. Percent cover is often estimated for total SAV, individual types of vegetation (seagrass, attached algae, drift algae) and individual species.
Frequency of Occurrence was calculated as the number of times a taxon was observed in a year divided by the number of sampling events, multiplied by 100. Analysis is conducted at the quadrat level and is inclusive of all quadrats (i.e., quadrats evaluated using Braun-Blanquet, modified Braun-Blanquet, and percent cover.”
Turtle grass (Thalassia testudinum) is the largest of the Florida seagrasses, with longer, thicker blades and deeper root structures than any of the other seagrasses. It is considered a climax seagrass species.
Shoal grass (Halodule wrightii) is an early colonizer of vegetated areas and usually grows in water too shallow for other species except widgeon grass. It can often tolerate larger salinity ranges than other seagrass species. Shoal grass is characterized by thin, flat blades, that are narrower than turtle grass blades.
Manatee grass (Syringodium filiforme) is easily recognizable because its leaves are thin and cylindrical instead of the flat, ribbon-like form shared by many other seagrass species. The leaves can grow up to half a meter in length. Manatee grass is usually found in mixed seagrass beds or small, dense monospecific patches.
Widgeon grass (Ruppia maritima) grows in both fresh and salt water and is widely distributed throughout Florida’s estuaries in less saline areas, particularly in inlets along the east coast. This species resembles shoal grass in certain environments but can be identified by the pointed tips of its leaves.
Three species of Halophila spp. are found in Florida - Star grass (Halophila engelmannii), Paddle grass (Halophila decipiens), and Johnson’s seagrass (Halophila johnsonii). These are smaller, more fragile seagrasses than other Florida species and are considered ephemeral. They grow along a single long rhizome, with short blades. These species are not well-studied, although surveys are underway to define their ecological roles.
Star grass, Paddle grass, and Johnson’s seagrass will be grouped together and listed as Halophila spp. in the following managed areas. This is because several surveys did not specify to the species level:
Banana River Aquatic Preserve
Indian River-Malabar to Vero Beach Aquatic Preserve
Indian River-Vero Beach to Ft. Pierce Aquatic Preserve
Jensen Beach to Jupiter Inlet Aquatic Preserve
Loxahatchee River-Lake Worth Creek Aquatic Preserve
Mosquito Lagoon Aquatic Preserve
Biscayne Bay Aquatic Preserve
Florida Keys National Marine Sanctuary
Click here to view spatio-temporal plots on GitHub.
Sampling locations by Program:
| ProgramID | N-Data | YearMin | YearMax | method | Sample Locations |
|---|---|---|---|---|---|
| 296 | 4200 | 1996 | 2021 | Braun Blanquet | 40 |
| 965 | 65538 | 2005 | 2011 | Braun Blanquet | 87 |
| 4018 | 3925 | 1999 | 2023 | Braun Blanquet | 115 |
| 4049 | 104563 | 2005 | 2024 | Braun Blanquet | 1267 |
| 4018 | 279 | 1999 | 2007 | Percent Cover | 67 |
Program names:
296 - Florida Keys National Marine Sanctuary Seagrass
Monitoring Project23
965 - South Florida Seagrass Fish and Invertebrate Assessment
Network18
4018 - Miami-Dade County DERM Benthic Habitat Monitoring
Program27
4018 - Miami-Dade County DERM Benthic Habitat Monitoring
Program27
4049 - The South Florida Fisheries Habitat Assessment Program
(FHAP)15
| CommonName | Trend Significance (0.05) | Period of Record | LME-Intercept | LME-Slope | p |
|---|---|---|---|---|---|
| Attached algae | No significant trend | 2008 - 2024 | 0.0761161 | -0.0025432 | 0.2165299 |
| Drift algae | Significantly decreasing trend | 1999 - 2024 | 9.1453632 | -0.2334903 | 0.0000182 |
| Shoal grass | Significantly decreasing trend | 1996 - 2024 | 7.0786462 | -0.2741281 | 0.0001016 |
| Halophila spp. | No significant trend | 2005 - 2024 | 0.0749728 | -0.0023143 | 0.3291618 |
| Widgeon grass | No significant trend | 2005 - 2024 | -0.0383108 | 0.0028175 | 0.1044281 |
| Manatee grass | Significantly decreasing trend | 1996 - 2024 | 4.9248479 | -0.1110174 | 0.0174460 |
| Turtle grass | Significantly decreasing trend | 1996 - 2024 | 43.8162349 | -1.4638927 | 0.0000000 |
| Total SAV | No significant trend | 1999 - 2024 | 31.5258442 | 0.2203815 | 0.1700662 |
| Total seagrass | Significantly increasing trend | 2005 - 2024 | 16.4149550 | 0.2503526 | 0.0067937 |
An annual increase in percent cover was observed for total seagrass (0.2%). Annual decreases in percent cover were observed for manatee grass (-0.1%), shoal grass (-0.3%), turtle grass (-1.5%), and drift algae (-0.2%). Total SAV, Halophila spp., widgeon grass, and attached algae showed no detectable change in percent cover.
The following parameters are available for Florida Keys National Marine Sanctuary within the SAV_WC_Report:
Colored Disolved Organic Matter
Chlorophyll a
Dissolved Oxygen
Dissolved Oxygen Saturation
pH
Salinity
Secchi Depth
Water Temperature
Total Nitrogen
Total Suspended Solids
Turbidity
Access the reports here: DRAFT_SAV_WC_Report_2024-11-20.pdf
The data file used is: All_CORAL_Parameters-2025-Mar-06.txt
Percent Cover
| Statistical Trend | Period of Record | LME Intercept | LME Slope | p |
|---|---|---|---|---|
| No significant trend | 1996 - 2021 | 4.96407 | -0.00233 | 0.05266 |
Percent cover showed no detectable trend between 1996 and 2021.
Species Richness
| Sample Count | Number of Years | Period of Record | Median N of Taxa | Mean N of Taxa |
|---|---|---|---|---|
| 11167 | 21 | 1999 - 2019 | 281 | 220.2253 |
The median annual number of taxa was 281 based on 11,167 observations collected between 1999 and 2019.
| Abudefduf saxatilis2 | Epinephelus morio2 | Padina gymnospora1 |
| Acanthemblemaria aspera2 | Epinephelus striatus2 | Pagrus pagrus2 |
| Acanthemblemaria chaplini2 | Eques lanceolatus2 | Palythoa mammillosa |
| Acanthemblemaria maria2 | Equetus punctatus2 | Palythoa spp. |
| Acanthemblemaria spinosa2 | Ernodesmis sp.1 | Pandaros acanthifolium |
| Acanthocybium solandri | Erylus formosus | Parablennius marmoreus2 |
| Acanthophora muscoides1 | Erythropodium caribaeorum3 | Paraclinus marmoratus2 |
| Acanthostracion polygonium2 | Eucinostomus argenteus | Paraclinus nigripinnis2 |
| Acanthostracion quadricornis2 | Eucinostomus gula | Paralichthys albigutta2 |
| Acanthurus bahianus2 | Eucinostomus jonesii | Paranthias furcifer2 |
| Acanthurus chirurgus2 | Eunicea calyculata3 | Pareques acuminatus2 |
| Acanthurus coeruleus2 | Eunicea flexuosa3 | Pareques umbrosus2 |
| Acanthurus sp.2 | Eunicea fusca3 | Pempheris schomburgkii2 |
| Acetabularia sp.1 | Eunicea knighti3 | Penaeus monodon |
| Acetabularia spp.1 | Eunicea laciniata3 | Penicillus sp.1 |
| Acropora cervicornis3 | Eunicea laxispica3 | Penicillus spp.1 |
| Acropora palmata3 | Eunicea mammosa3 | Peyssonnelia |
| Acropora prolifera3 | Eunicea palmeri3 | Phaeoptyx xenus2 |
| Actiniaria | Eunicea succinea3 | Phorbas sp. |
| Aetobatus narinari | Eunicea tourneforti3 | Phyllangia americana3 |
| Agardhiella ramosissima1 | Eusmilia fastigiata3 | Phymanthus crucifer |
| Agaricia agaricites3 | Euthynnus alletteratus | Plakortis angulospiculatus |
| Agaricia fragilis3 | Favia fragum3 | Plexaura homomalla3 |
| Agaricia grahamae3 | Fine turf | Plexaura kuna3 |
| Agaricia humilis3 | Fistularia tabacaria2 | Plexaurella dichotoma3 |
| Agaricia lamarcki3 | Fowlerichthys ocellatus2 | Plexaurella grandiflora3 |
| Agaricia sp. | Galaxaura spp. | Plexaurella grisea3 |
| Agaricia spp.3 | Galeocerdo cuvier2 | Plexaurella nutans3 |
| Agaricia tenuifolia | Geodia gibberosa | Polysiphonia sp.1 |
| Agaricia undata3 | Geodia neptuni | Pomacanthus arcuatus2 |
| Agelas clathrodes | Gerres cinereus | Pomacanthus paru2 |
| Agelas conifera | Ginglymostoma cirratum | Porifera |
| Agelas dispar | Gnatholepis thompsoni2 | Porifera spp. |
| Agelas schmidtii | Gobioclinus bucciferus2 | Porites astreoides3 |
| Agelas wiedenmayeri | Gobioclinus filamentosus2 | Porites branneri3 |
| Ahlia egmontis | Gobioclinus gobio2 | Porites cf. branneri |
| Aiolochroia crassa | Gobioclinus kalisherae2 | Porites colonensis3 |
| Albula vulpes | Gobiosoma sp.2 | Porites divaricata3 |
| Alcyonacea sp.3 | Gorgonia flabellum3 | Porites furcata3 |
| Alectis ciliaris2 | Gorgonia mariae3 | Porites porites3 |
| Alphestes afer2 | Gorgonia ventalina3 | Porites sp. |
| Aluterus monoceros2 | Gracilaria sp.1 | Porites spp.3 |
| Aluterus schoepfii2 | Gramma loreto2 | Priacanthus arenatus2 |
| Aluterus scriptus2 | Grateloupia1 | Priolepis hipoliti2 |
| Aluterus sp.2 | Griffithsia1 | Prionotus ophryas2 |
| Amblycirrhitus pinos2 | Gymnothorax funebris2 | Prionotus rubio2 |
| Amphimedon compressa | Gymnothorax miliaris2 | Pristipomoides aquilonaris2 |
| Amphimedon viridis | Gymnothorax moringa2 | Pristis pectinata |
| Amphiroa spp.1 | Gymnothorax nigromarginatus2 | Prognathodes aculeatus2 |
| Anadyomene linkiana1 | Gymnothorax saxicola2 | Pseudobatos lentiginosus |
| Anadyomene spp.1 | Gymnothorax vicinus2 | Pseudodiploria clivosa3 |
| Anadyomene stellata1 | Haemulon album2 | Pseudodiploria strigosa3 |
| Anchoa lyolepis | Haemulon aurolineatum2 | Pseudoplexaura crucis3 |
| Anisotremus surinamensis2 | Haemulon carbonarium2 | Pseudoplexaura flagellosa3 |
| Anisotremus virginicus2 | Haemulon flavolineatum2 | Pseudoplexaura porosa3 |
| Antillogorgia acerosa3 | Haemulon macrostomum2 | Pseudoplexaura wagenaari3 |
| Antillogorgia americana3 | Haemulon melanurum2 | Pseudupeneus maculatus2 |
| Antillogorgia bipinnata3 | Haemulon parra2 | Ptereleotris calliura |
| Antillogorgia kallos3 | Haemulon plumierii2 | Ptereleotris helenae |
| Antillogorgia rigida3 | Haemulon sciurus2 | Pterocladiella sanctarum1 |
| Aplysina archeri | Haemulon sp.2 | Pterogorgia anceps3 |
| Aplysina cauliformis | Haemulon striatum2 | Pterogorgia citrina3 |
| Aplysina fistularis | Haemulon vittatum2 | Pterogorgia guadalupensis3 |
| Aplysina fulva | Halichoeres bivittatus2 | Pterois miles2 |
| Aplysina lacunosa | Halichoeres caudalis2 | Pterois volitans2 |
| Apogon aurolineatus2 | Halichoeres cyanocephalus2 | Ptilocaulis sp. |
| Apogon binotatus2 | Halichoeres garnoti2 | Rachycentron canadum |
| Apogon maculatus2 | Halichoeres maculipinna2 | Ramicrusta spp. |
| Apogon phenax2 | Halichoeres pictus2 | Razorfish sp.2 |
| Apogon pseudomaculatus2 | Halichoeres poeyi2 | Red calcareous branching algae |
| Apogon quadrisquamatus2 | Halichoeres radiatus2 | Red frondose algae |
| Apogon townsendi2 | Haliclona (Reneira) aquaeductus | Remora remora |
| Archosargus probatocephalus2 | Haliclona (Reniera) tubifera | Rhinoptera bonasus |
| Archosargus rhomboidalis2 | Haliclona sp. | Rhipocephalus1 |
| Arturia canariensis | Halimeda spp.1 | Rhipocephalus phoenix1 |
| Astrapogon puncticulatus2 | Halisarca sp. | Rhipocephalus spp.1 |
| Astrapogon sp.2 | Halodule wrightii1 | Rhodactis osculifera |
| Astrapogon stellatus2 | Halophila decipiens1 | Rhomboplites aurorubens2 |
| Astroscopus guttatus | Halophila engelmannii1 | Ricordea florida |
| Atherinomorus stipes | Halophila johnsonii1 | Rubble |
| Aulostomus maculatus2 | Halophila sp.1 | Ruppia maritima1 |
| Avrainvillea levis1 | Harengula humeralis | Rypticus bistrispinus2 |
| Axinellida | Harengula jaguana | Rypticus maculatus2 |
| Azurina cyanea2 | Helioseris cucullata3 | Rypticus saponaceus2 |
| Balistes capriscus2 | Hemiemblemaria simula2 | Sand-sand |
| Balistes sp.2 | Hemiramphus brasiliensis | Sand on hard-bottom |
| Balistes vetula2 | Heteroconger longissimus | Sardinella aurita |
| Bare substrate | Heteropriacanthus cruentatus2 | Sargassum sp.1 |
| Bartholomea annulata | Higginsia strigilata | Sargassum spp.1 |
| Batophora oerstedii1 | Hippocampus erectus2 | Sargocentron bullisi2 |
| Batophora spp.1 | Hippocampus reidi2 | Sargocentron coruscum2 |
| Blenniidae sp.2 | Hippospongia sp. | Sargocentron vexillarium2 |
| Bodianus pulchellus2 | Holacanthus bermudensis2 | Scartella cristata2 |
| Bodianus rufus2 | Holacanthus ciliaris2 | Scarus coelestinus2 |
| Bollmannia boqueronensis2 | Holacanthus tricolor2 | Scarus coeruleus2 |
| Bothus lunatus2 | Holocentrus adscensionis2 | Scarus guacamaia2 |
| Bothus ocellatus2 | Holocentrus rufus2 | Scarus iseri2 |
| Brachygenys chrysargyreum2 | Hydrozoa | Scarus sp.2 |
| Branching gorgonian3 | Hypanus americanus | Scarus taeniopterus2 |
| Briareum asbestinum3 | Hypleurochilus bermudensis2 | Scarus vetula2 |
| Brockius nigricinctus2 | Hypnea1 | Schizothrix calcicola |
| Brotula barbata | Hypoatherina harringtonensis | Schultzea beta2 |
| Brown algae1 | Hypoglossum1 | Scianid sp.2 |
| Bryopsis1 | Hypoplectrus chlorurus2 | Scleractinia3 |
| Bryozoa | Hypoplectrus gemma2 | Scolymia cubensis3 |
| Calamus bajonado2 | Hypoplectrus gummigutta2 | Scolymia lacera |
| Calamus calamus2 | Hypoplectrus guttavarius2 | Scolymia sp.3 |
| Calamus leucosteus2 | Hypoplectrus hybrid2 | Scolymia spp.3 |
| Calamus nodosus2 | Hypoplectrus indigo2 | Scomberomorus cavalla |
| Calamus penna2 | Hypoplectrus nigricans2 | Scomberomorus maculatus |
| Calamus proridens2 | Hypoplectrus puella2 | Scomberomorus regalis |
| Calcareous green algae1 | Hypoplectrus sp.2 | Scopalina ruetzleri |
| Callionymus bairdi2 | Hypoplectrus tann2 | Scorpaena plumieri2 |
| Callyspongia (Callyspongia) fallax | Hypoplectrus unicolor2 | Scorpaenodes caribbaeus2 |
| Callyspongia (Cladochalina) aculeata | Hyporthodus flavolimbatus2 | Selachii |
| Callyspongia (Cladochalina) plicifera | Hyporthodus niveatus2 | Selene vomer2 |
| Callyspongia (Cladochalina) tenerrima | Hyrtios violaceus | Seriola dumerili2 |
| Calyx podatypa | Iciligorgia schrammi3 | Seriola rivoliana2 |
| Cantherhines macrocerus2 | Iotrochota birotulata | Seriola sp.2 |
| Cantherhines pullus2 | Ircinia campana | Seriola zonata2 |
| Canthidermis sufflamen2 | Ircinia felix | Serranid sp.2 |
| Canthigaster rostrata2 | Ircinia strobilina | Serranus annularis2 |
| Caranx bartholomaei2 | Ircinia variabilis | Serranus baldwini2 |
| Caranx crysos2 | Isophyllia rigida3 | Serranus phoebe2 |
| Caranx hippos2 | Isophyllia sinuosa3 | Serranus subligarius2 |
| Caranx latus2 | Isophyllia sp. | Serranus tabacarius2 |
| Caranx lugubris2 | Istiophorus platypterus | Serranus tigrinus2 |
| Caranx ruber2 | Jania spp.1 | Serranus tortugarum2 |
| Caranx sp.2 | Jenkinsia sp. | Siderastrea radians3 |
| Carcharhinus falciformis | Kallymenia spp. | Siderastrea siderea3 |
| Carcharhinus leucas | Kyphosus sectatrix2 | Siderastrea sp. |
| Carcharhinus limbatus | Labrisomidae sp.2 | Siderastrea spp. |
| Carcharhinus obscurus | Labrisomus nuchipinnis2 | Silt on hard-bottom |
| Carcharhinus perezii | Lachnolaimus maximus2 | Siphonodictyon coralliphagum |
| Carcharhinus plumbeus | Lactophrys bicaudalis2 | Siphonodictyon siphonum |
| Caulerpa spp.1 | Lactophrys trigonus2 | Snapper sp.2 |
| Centroceras sp.1 | Lactophrys triqueter2 | Solenastrea bournoni3 |
| Centropomus undecimalis | Lagodon rhomboides2 | Solenastrea hyades3 |
| Centropristis ocyurus2 | Laurencia spp.1 | Solenastrea sp. |
| Centropristis striata2 | Lebrunia neglecta | Solenastrea spp.3 |
| Centropyge argi2 | Liagora spp. | Sparidae sp.2 |
| Cephalopholis cruentata2 | Liopropoma eukrines2 | Sparisoma atomarium2 |
| Cephalopholis fulva2 | Liopropoma mowbrayi2 | Sparisoma aurofrenatum2 |
| Ceramium1 | Liopropoma rubre2 | Sparisoma chrysopterum2 |
| Chaenopsis limbaughi2 | Lobophora spp. | Sparisoma radians2 |
| Chaetodipterus faber | Lutjanus analis2 | Sparisoma rubripinne2 |
| Chaetodon capistratus2 | Lutjanus apodus2 | Sparisoma sp.2 |
| Chaetodon ocellatus2 | Lutjanus buccanella2 | Sparisoma viride2 |
| Chaetodon sedentarius2 | Lutjanus campechanus2 | Spermothamnion1 |
| Chaetodon striatus2 | Lutjanus cyanopterus2 | Spheciospongia vesparium |
| Chaetomorpha linum1 | Lutjanus griseus2 | Sphoeroides2 |
| Champia parvula1 | Lutjanus jocu2 | Sphoeroides nephelus2 |
| Chara spp.1 | Lutjanus mahogoni2 | Sphoeroides spengleri2 |
| Chilomycterus antennatus2 | Lutjanus synagris2 | Sphoeroides testudineus2 |
| Chilomycterus reticulatus2 | Macroalgae | Sphyraena barracuda2 |
| Chilomycterus schoepfii2 | Madracis auretenra3 | Sphyraena guachancho |
| Chloroscombrus chrysurus2 | Madracis carmabi3 | Sphyraena picudilla |
| Chondria capillaris1 | Madracis decactis3 | Sphyrna lewini |
| Chondrilla nucula | Madracis formosa3 | Sphyrna mokarran |
| Chondrosia sp. | Madracis myriaster3 | Sphyrna tiburo |
| Chriodorus atherinoides | Madracis senaria3 | Spirastrella coccinea |
| Chromis enchrysurus2 | Madracis sp. | Spirastrella mollis |
| Chromis insolata2 | Madracis spp.3 | Spongia sp. |
| Chromis multilineata2 | Malacanthus plumieri | Spyridia filamentosa1 |
| Chromis scotti2 | Malacoctenus aurolineatus2 | Squirrelfish sp.2 |
| Cinachyra sp. | Malacoctenus gilli2 | Stegastes adustus2 |
| Cladocephalus1 | Malacoctenus macropus2 | Stegastes diencaeus2 |
| Cladocora arbuscula3 | Malacoctenus triangulatus2 | Stegastes leucostictus2 |
| Cladophora1 | Malacoctenus versicolor2 | Stegastes partitus2 |
| Clathria (Thalysias) venosa | Manicina areolata3 | Stegastes planifrons2 |
| Clathria (Thalysias) virgultosa | Meandrina jacksoni | Stegastes sp.2 |
| Clathria sp. | Meandrina meandrites3 | Stegastes variabilis2 |
| Clepticus parrae2 | Megalops atlanticus | Stephanocoenia intersepta3 |
| Cliona caribbaea | Melichthys niger2 | Stephanolepis hispida2 |
| Cliona delitrix | Menidia sp. | Stichodactyla helianthus |
| Cliona sp. | Microgobius carri2 | Strongylacidon sp. |
| Cliona spp. | Microgobius microlepis2 | Strongylura notata2 |
| Cliona varians | Microspathodon chrysurus2 | Strongylura timucu |
| Colpophyllia natans3 | Millepora alcicornis3 | Stygnobrotula latebricola |
| Colpophyllia spp.3 | Millepora complanata3 | Stypopodium spp. |
| Condylactis gigantea | Millepora spp.3 | Substrate |
| Corallimorpharians | Mobula birostris | Syacium micrurum2 |
| Coralliophila erosa | Monacanthus ciliatus2 | Syngnathus scovelli2 |
| Coryphopterus dicrus2 | Monacanthus tuckeri2 | Syngnathus sp.2 |
| Coryphopterus eidolon2 | Monanchora arbuscula | Synodus foetens2 |
| Coryphopterus glaucofraenum2 | Montastraea cavernosa3 | Synodus intermedius2 |
| Coryphopterus lipernes2 | Mulloidichthys martinicus2 | Synodus synodus2 |
| Coryphopterus personatus2 | Muraena retifera2 | Syringodium filiforme1 |
| Coryphopterus punctipectophorus2 | Muricea atlantica3 | Tectitethya crypta |
| Coryphopterus sp.2 | Muricea elongata3 | Tedania (Tedania) ignis |
| Cribrochalina vasculum | Muricea laxa3 | Tethya diploderma |
| Crustose coralline algae1 | Muricea muricata3 | Thalassia testudinum1 |
| Cryptotomus roseus2 | Muricea pinnata3 | Thalassoma bifasciatum2 |
| Ctenogobius saepepallens2 | Muriceopsis flavida3 | Thick turf |
| Cyanobacteria | Mussa angulosa3 | Tigrigobius macrodon2 |
| Cyanophyta spp. | Mycale (Mycale) laevis | Tigrigobius saucrus2 |
| Dactylopterus volitans | Mycale sp. | Total brown algae1 |
| Dasya sp.1 | Mycetophyllia aliciae3 | Total calcareous green algae1 |
| Dasycladus1 | Mycetophyllia danaana3 | Total green algae1 |
| Decapterus macarellus2 | Mycetophyllia ferox3 | Total macroalgae1 |
| Decapterus punctatus2 | Mycetophyllia lamarckiana3 | Total other green algae1 |
| Decapterus sp.2 | Mycetophyllia sp. | Total other red algae1 |
| Dendrogyra cylindrus3 | Mycetophyllia spp.3 | Total SAV1 |
| Derbesia1 | Mycteroperca acutirostris2 | Total seagrass1 |
| Dermatolepis inermis2 | Mycteroperca bonaci2 | Trachinotus falcatus2 |
| Desmapsamma anchorata | Mycteroperca interstitialis2 | Trachinotus goodei2 |
| Diadema antillarum | Mycteroperca microlepis2 | Trachurus lathami2 |
| Dichocoenia stokesii3 | Mycteroperca phenax2 | Trachyteleia hispida |
| Dictyosphaeria1 | Mycteroperca tigris2 | Tunicata |
| Dictyota spp.1 | Mycteroperca venenosa2 | Turbinaria turbinata |
| Diodon holocanthus2 | Myrichthys breviceps | Turf algae free of sediment |
| Diodon hystrix2 | Myrichthys ocellatus | Turf algae with sediment |
| Diodon sp.2 | Myripristis jacobus2 | Tylosurus crocodilus |
| Diplastrella megastellata | Narcine bancroftii | Udotea1 |
| Diplectrum formosum2 | Needlefish sp. | Udotea spp.1 |
| Diplodus argenteus2 | Negaprion brevirostris | Ulaema lefroyi |
| Diplodus holbrookii2 | Neofibularia nolitangere | Ulva sp.1 |
| Diploria labyrinthiformis3 | Neomeris1 | Umbrina coroides2 |
| Diploria sp. | Neoniphon marianus2 | Undaria sp. |
| Diploria spp.3 | Neopetrosia carbonaria | Unidentified mangrove |
| Discosoma carlgreni | Nes longus2 | Unidentified species |
| Doratonotus megalepis2 | Nicholsina usta2 | Unknown black smooth encrusting sponge |
| Dragmacidon lunaecharta | Niphates amorpha | Unknown bowling ball sponge |
| Drift red algae1 | Niphates digitalis | Unknown brown encrusting sponge |
| Dysidea etheria | Niphates erecta | Unknown brown smooth sponge |
| Dysidea fragilis | Octocorallia3 | Unknown brown tube sponge |
| Dysidea janiae | Oculina diffusa3 | Unknown brown vein sponge |
| Echeneis naucrates | Oculina robusta3 | Unknown green encrusting sponge |
| Echeneis neucratoides | Oculina sp. | Unknown olive sponge |
| Echinoidea | Ocyurus chrysurus2 | Unknown orange encrusting sponge |
| Ectyoplasia ferox | Odontoscion dentex2 | Unknown orange massive sponge |
| Elacatinus dilepis2 | Ogcocephalus nasutus2 | Unknown pink lumpy sponge |
| Elacatinus evelynae2 | Ogcocephalus sp. | Unknown red encrusting sponge |
| Elacatinus horsti2 | Oligoplites saurus2 | Unknown red lumpy tube sponge |
| Elacatinus oceanops2 | Ophioblennius macclurei2 | Unknown red squishy sponge |
| Elacatinus randalli2 | Opistognathus aurifrons | Upeneus parvus2 |
| Elacatinus xanthiprora2 | Opistognathus macrognathus | Urobatis jamaicensis |
| Elagatis bipinnulata2 | Opistognathus sp. | Valonia1 |
| Elops saurus | Opistognathus whitehursti | Verongula gigantea |
| Emblemaria pandionis2 | Opsanus tau2 | Verongula reiswigi |
| Emblemariopsis bahamensis2 | Orbicella annularis3 | Verongula rigida |
| Emmelichthyops atlanticus2 | Orbicella faveolata3 | Wrightiella1 |
| Enchelycore carychroa2 | Orbicella franksi3 | Xestospongia muta |
| Enchelycore nigricans2 | Orbicella sp. | Xyrichtys martinicensis2 |
| Encrusting gorgonian3 | Orthopristis chrysoptera2 | Xyrichtys novacula2 |
| Enneanectes altivelis | Other calcareous macroalgae | Xyrichtys splendens2 |
| Enneanectes boehlkei | Other coral | Zanclus cornutus |
| Epinephelus adscensionis2 | Other fleshy macroalgae | Zoanthidae |
| Epinephelus drummondhayi2 | Other green algae1 | Zoanthids |
| Epinephelus guttatus2 | Other red algae1 | Abudefduf saxatilis2 |
| Epinephelus itajara2 | Oxyurichthys stigmalophius2 | Acanthemblemaria aspera2 |
1 - Submerged Aquatic Vegetation, 2 - Coral Reef - Species Richness, 3 - Coral Reef - Percent Cover